✨Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents

📝 Summary:
This paper proposes that cognitive models and AI algorithms provide templates for designing modular language agents. These agent templates specify roles and functional composition to combine large language models for complex tasks, leading to more effective and interpretable systems.

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.22523
• PDF: https://arxiv.org/pdf/2602.22523

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✨Spectral Condition for μP under Width-Depth Scaling

📝 Summary:
This paper presents a unified spectral framework for maximal update parameterization addressing stable feature learning and hyperparameter transfer in deep neural networks scaled in both width and depth. It introduces a spectral condition for weight scaling that unifies existing formulations and ...

🔹 Publication Date: Published on Feb 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00541
• PDF: https://arxiv.org/pdf/2603.00541
• Project Page: https://github.com/ML-GSAI/Width-Depth-muP
• Github: https://github.com/ML-GSAI/Width-Depth-muP

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✨CC-VQA: Conflict- and Correlation-Aware Method for Mitigating Knowledge Conflict in Knowledge-Based Visual Question Answering

📝 Summary:
CC-VQA addresses knowledge conflicts in visual question answering by incorporating visual-semantic conflict analysis and correlation-guided encoding-decoding mechanisms without requiring model retrain...

🔹 Publication Date: Published on Feb 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23952
• PDF: https://arxiv.org/pdf/2602.23952
• Github: https://github.com/cqu-student/CC-VQA

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✨VGGT-Det: Mining VGGT Internal Priors for Sensor-Geometry-Free Multi-View Indoor 3D Object Detection

📝 Summary:
VGGT-Det enables sensor-geometry-free multi-view indoor 3D object detection. It integrates a Visual Geometry Grounded Transformer, using Attention-Guided Query Generation and Query-Driven Feature Aggregation to leverage VGGT's internal semantic and geometric priors. This approach significantly ou...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00912
• PDF: https://arxiv.org/pdf/2603.00912
• Github: https://github.com/yangcaoai/VGGT-Det-CVPR2026

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✨LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model

📝 Summary:
LLaDA-o is an omni diffusion model that uses a Mixture of Diffusion framework to jointly handle text understanding and visual generation through a shared attention backbone, achieving state-of-the-art...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01068
• PDF: https://arxiv.org/pdf/2603.01068
• Github: https://github.com/ML-GSAI/LLaDA-o

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✨Tool-R0: Self-Evolving LLM Agents for Tool-Learning from Zero Data

📝 Summary:
Tool-R0 framework enables training general-purpose tool-calling agents through self-play reinforcement learning without initial datasets, achieving significant performance improvements over base model...

🔹 Publication Date: Published on Feb 24

🔹 Paper Links:
• arXiv Page: https://huggingface.co/collections/emrecanacikgoz/tool-r0
• PDF: https://arxiv.org/pdf/2602.21320
• Project Page: https://emrecanacikgoz.github.io/Tool-R0/
• Github: https://github.com/emrecanacikgoz/Tool-R0

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✨Half-Truths Break Similarity-Based Retrieval

📝 Summary:
CLIP-style models exhibit vulnerabilities to half-truths where incorrect details can increase similarity scores, which is addressed through component-supervised fine-tuning that improves compositional...

🔹 Publication Date: Published on Feb 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23906
• PDF: https://arxiv.org/pdf/2602.23906
• Github: https://github.com/kargibora/CS-CLIP

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✨Legal RAG Bench: an end-to-end benchmark for legal RAG

📝 Summary:
Legal RAG Bench evaluates legal retrieval-augmented generation systems using a comprehensive dataset and factorial analysis, revealing that information retrieval significantly impacts performance more...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01710
• PDF: https://arxiv.org/pdf/2603.01710
• Project Page: https://isaacus.com/blog/legal-rag-bench
• Github: https://github.com/isaacus-dev/legal-rag-bench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/isaacus/legal-rag-bench

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✨RubricBench: Aligning Model-Generated Rubrics with Human Standards

📝 Summary:
RubricBench is introduced as a benchmark for evaluating rubric-guided reward models in large language model alignment, addressing the lack of discriminative complexity and ground-truth annotations in ...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01562
• PDF: https://arxiv.org/pdf/2603.01562
• Project Page: https://huggingface.co/datasets/DonJoey/rubricbench
• Github: https://github.com/planepig/rubricbench

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✨OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens

📝 Summary:
OmniLottie framework generates high-quality vector animations from multi-modal instructions using a specialized Lottie tokenizer and pretrained vision-language models. AI-generated summary Omni Lottie...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02138
• PDF: https://arxiv.org/pdf/2603.02138
• Project Page: https://openvglab.github.io/OmniLottie/
• Github: https://github.com/OpenVGLab/OmniLottie

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✨LaSER: Internalizing Explicit Reasoning into Latent Space for Dense Retrieval

📝 Summary:
LaSER introduces a self-distillation framework that embeds explicit reasoning into dense retrievers' latent space through dual-view training and multi-grained alignment, enabling efficient reasoning w...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01425
• PDF: https://arxiv.org/pdf/2603.01425

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✨When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains

📝 Summary:
Reinforcement learning enhances medical vision-language model performance primarily by sharpening output distributions when models already have sufficient reasoning support, with supervised fine-tunin...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01301
• PDF: https://arxiv.org/pdf/2603.01301
• Project Page: https://medbridgerl.github.io/
• Github: https://github.com/armenjeddi/medbridgerl

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✨RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment

📝 Summary:
RAISE is a training-free, requirement-driven evolutionary framework that adaptively improves text-to-image generation by dynamically allocating computational resources based on prompt complexity throu...

🔹 Publication Date: Published on Feb 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.00483
• PDF: https://arxiv.org/pdf/2603.00483
• Github: https://github.com/LiyaoJiang1998/RAISE

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✨CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production

📝 Summary:
CharacterFlywheel is an iterative optimization process that enhances large language models for social chat applications through multiple generations of refinement, achieving significant improvements i...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01973
• PDF: https://arxiv.org/pdf/2603.01973

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✨Agentic Code Reasoning

📝 Summary:
LLM agents can perform code reasoning tasks like patch verification, fault localization, and code QA with improved accuracy through structured semi-formal reasoning that requires explicit premises and...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01896
• PDF: https://arxiv.org/pdf/2603.01896

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✨FireRed-OCR Technical Report

📝 Summary:
FireRed-OCR transforms general vision-language models into specialized OCR systems through structured data synthesis and progressive training strategies. AI-generated summary We present FireRed-OCR, a...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01840
• PDF: https://arxiv.org/pdf/2603.01840
• Github: https://github.com/FireRedTeam/FireRed-OCR

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✨MMR-Life: Piecing Together Real-life Scenes for Multimodal Multi-image Reasoning

📝 Summary:
MMR-Life is a new benchmark assessing multimodal large language models reasoning across real-life scenarios using diverse multi-image questions. It features 2,646 questions on 19,108 real-world images covering seven reasoning types. Top models like GPT-5 only achieve 58 percent accuracy, showing ...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02024
• PDF: https://arxiv.org/pdf/2603.02024
• Project Page: https://mmr-life-bench.github.io/
• Github: https://github.com/BugMakerzzz/MMR-Life

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Septzzz/MMR-Life

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✨CoVe: Training Interactive Tool-Use Agents via Constraint-Guided Verification

📝 Summary:
CoVe is a post-training data synthesis framework that generates high-quality training trajectories for interactive tool-use agents by incorporating task constraints as verification mechanisms, achievi...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01940
• PDF: https://arxiv.org/pdf/2603.01940
• Project Page: https://cove-agent.github.io

🔹 Models citing this paper:
• https://huggingface.co/Zichen1024/CoVe-4B

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Zichen1024/CoVe-12k

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✨Learn Hard Problems During RL with Reference Guided Fine-tuning

📝 Summary:
Reference-Guided Fine-Tuning (ReGFT) addresses reward sparsity in reinforcement learning for mathematical reasoning by using human-written solutions to create guided training trajectories that improve...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01223
• PDF: https://arxiv.org/pdf/2603.01223

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✨Tool Verification for Test-Time Reinforcement Learning

📝 Summary:
Test-time reinforcement learning with tool verification addresses consensus bias in large reasoning models by using external validation to improve reward estimation and model stability. AI-generated s...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.02203
• PDF: https://arxiv.org/pdf/2603.02203

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✨ArtLLM: Generating Articulated Assets via 3D LLM

📝 Summary:
ArtLLM generates articulated 3D assets from meshes using a 3D multimodal large language model that predicts part layouts and joints while synthesizing high-fidelity geometries. AI-generated summary Cr...

🔹 Publication Date: Published on Mar 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01142
• PDF: https://arxiv.org/pdf/2603.01142

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